Syllabus of B.tech. III SEM AIML (RGPV)

Source: (rgpv.ac.in)

  • Understanding the process and scope of Communication
  • Relevance & Importance of Communication in a Globalized world
  • Forms of Communication
  • Role of Unity Brevity and Clarity in various forms of communication
  • Verbal & Non-verbal Communication
  • Classification of NVC
  • Barriers to Communication
  • Communicating Globally
  • Culture and Communication.
  • Soft Skills: Interpersonal Communication
  • Listening Persuasion Negotiation
  • Communicating bad news/messages
  • communicating in a global world.
  • Traits of Technical Writing
  • Principles of Business Writing
  • Style of Writing Writing Memos
  • Letters Reports and Types of technical reports
  • Characteristics format and structure of technical reports
  • Writing Research Papers.
  • Speaking Skills: Audience-awareness Voice Vocabulary and Paralanguage
  • Group Discussion Combating Nervousness
  • Speaking to one and to one thousand
  • Mock Presentations.
  • Preparing for interviews assessing yourself
  • Drafting Effective Resume Dress decorum and Delivery techniques
  • Techniques of handling interviews
  • Use of Nonverbals during Interviews
  • Handling turbulence during interviews.
  • Group Discussion: Objective Method Focus Content
  • Style and Argumentation skills.
  • Professional Presentations: Individual Presentations (Audience Awareness
  • Body Language
  • Delivery and Content of Presentation.
  • Basics of grammar
  • common error in writing and speaking
  • Study of advanced grammar
  • Vocabulary Pronunciation Etiquette Syllables
  • Vowel sounds Consonant sounds
  • Tone: Rising tone Falling Tone
  • Flow in Speaking Speaking with a purpose
  • Speech & personality
  • Professional Personality Attributes

 

Source: (rgpv.ac.in)

  • Probability spaces conditional probability independence;
  • Discrete random variables Independent random variables
  • the multinomial distribution
  • Poisson approximation to the binomial distribution
  • infinite sequences of Bernoulli trials
  • sums of independent random variables;
  • Expectation of Discrete Random Variables
  • Moments Variance of a sum
  • Correlation coefficient
  • Chebyshev’s Inequality.
  • Continuous random variables and their properties
  • distribution functions and densities
  • normal exponential and gamma densities.
  • Bivariate distributions and their properties
  • distribution of sums and quotients
  • conditional densities
  • Bayes’ rule.
  • Measures of Central tendency: Moments skewness and Kurtosis –
  • Probability distributions: Binomial
  • Poisson and Normal – evaluation of statistical parameters for these three distributions
  • Correlation and regression – Rank correlation.
  • Curve fitting by the method of least squares- fitting of straight lines
  • second degree parabolas and more general curves.
  • Test of significance: Large sample test for single proportion
  • difference of proportions
  • single mean difference of means and difference of standard deviations.
  • Test for single mean difference of means and correlation coefficients
  • test for ratio of variances – Chi-square test for goodness of fit and independence of attributes.

 

Source: (rgpv.ac.in)

  • Concepts of Data and Information
  • Classification of Data structures
  • Abstract Data Types
  • Implementation aspects: Memory representation.
  • Data structures operations and its cost estimation.
  • Introduction to linear data structures- Arrays
  • Linked List: Representation of linked list in memory
  • different implementation of linked list. Circular linked list doubly linked list etc.
  • Application of linked list: polynomial manipulation using linked list etc.
  • Stacks as ADT Different implementation of stack multiple stacks.
  • Application of Stack: Conversion of infix to postfix notation using stack
  • evaluation of postfix expression
  • Recursion. Queues: Queues as ADT
  • Different implementation of queue Circular queue
  • Concept of D queue and Priority Queue Queue simulation Application of queues.
  • Definitions – Height depth order degree etc.
  • Binary Search Tree – Operations Traversal Search.
  • AVL Tree Heap
  • Applications and comparison of various types of tree;
  • Introduction to forest multi-way Tree B tree B+ tree B* tree and red-black tree.
  • Introduction
  • Classification of graph: Directed and Undirected graphs etc
  • Representation Graph Traversal: Depth First Search (DFS) Breadth First Search (BFS)
  • Graph algorithm: Minimum Spanning Tree (MST)-Kruskal Prim’s algorithms.
  • Dijkstra’s shortest path algorithm; Comparison between different graph algorithms.
  • Application of graphs.
  • Introduction
  • Sort methods like: Bubble Sort Quick sort.
  • Selection sort Heap sort Insertion sort Shell sort Merge sort and Radix sort;
  • comparison of various sorting techniques.
  • Searching: Basic Search Techniques: Sequential search Binary search
  • Comparison of search methods.
  • Hashing & Indexing.
  • Case Study: Application of various data structures in operating system DBMS etc.

 

Source: (rgpv.ac.in)

  • Fundamental of Artificial Intelligence history
  • motivation and need of AI
  • Production systems Characteristics of production systems
  • goals and contribution of AI to modern technology
  • search space different search techniques: hill Climbing Best first Search heuristic search algorithm A* and AO* search techniques etc.
  • Knowledge Representation Problems in representing knowledge
  • knowledge representation using propositional and predicate logic
  • comparison of propositional and predicate logic
  • Resolution refutation deduction
  • theorem proving inferencing
  • monotonic and non-monotonic reasoning.
  • Probabilistic reasoning
  • Baye’s theorem
  • semantic networks scripts schemas frames
  • conceptual dependency
  • forward and backward reasoning.
  • Game playing techniques like minimax procedure alpha-beta cut-offs etc
  • planning Study of the block world problem in robotics
  • Introduction to understanding
  • natural language processing (NLP)
  • Components of NLP
  • application of NLP to design expert systems.
  • Expert systems (ES) and its Characteristics requirements of ES
  • components and capability of expert systems
  • Inference Engine Forward & backward Chaining
  • Expert Systems Limitation
  • Expert System Development Environment technology
  • Benefits of Expert Systems.

 

Source: (rgpv.ac.in)

  • Introduction to Object Oriented Thinking & Object Oriented Programming: Comparison with Procedural Programming
  • features of Object oriented paradigm– Merits and demerits of OO methodology;
  • Object model;
  • Elements of OOPS
  • IO processing
  • Data Type Type Conversion
  • Control Statement
  • Loops Arrays.
  • Encapsulation and Data Abstraction-
  • Concept of Objects: State Behavior & Identity of an object;
  • Classes: identifying classes and candidates for Classes Attributes and Services
  • Access modifiers
  • Static members of a Class Instances
  • Message passing and Construction and destruction of Objects.
  • Relationships – Inheritance: purpose and its types ‘is a’ relationship;
  • Association
  • Aggregation.
  • Concept of interfaces and Abstract classes.
  • Polymorphism: Introduction
  • Method Overriding & Overloading
  • static and run time Polymorphism.
  • Virtual Function friend function Static function
  • friend class.
  • Strings
  • Exceptional handling
  • Introduction of Multi-threading and Data collections.
  • Case study like: ATM Library management system.

 

Source: (rgpv.ac.in)

  • Introduction to python language
  • Basic syntax
  • Literal Constants Numbers
  • Variable and Basic data types
  • String Escape Sequences
  • Operators and Expressions Evaluation Order Indentation
  • Input Output Functions Comments..
  • Data Structure: List Tuples Dictionary
  • Data Frame and Sets
  • constructing indexing
  • slicing and content manipulation
  • Control Flow: Conditional Statements – If If-else Nested If-else.
  • Iterative Statement – For While Nested Loops.
  • Control statements – Break Continue Pass.
  • Object oriented programming: Class and Object
  • Attributes Methods
  • Scopes and Namespaces
  • Inheritance
  • Overloading Overriding
  • Data hiding Exception: Exception Handling Except clause Try finally clause
  • User Defined Exceptions.
  • Modules and Packages: Standard Libraries: File I/0 Sys logging
  • Regular expression Date and Time
  • Network programming
  • multi-processing and multithreading.